Disneyland Inside Out for iPhone

Disneyland Inside Out for iPhone is imrlabs latest mobile project, bringing content from the popular Disneyland Inside Out web site to users on the Apple iPhone devices. This project let us dig deep into the world of iPhone development, linking RESTful web services to a rich native client. This App provides a deep connection to Facebook and Gowalla, along with a direct connection to the content managed on the web through DotNetNuke.

RESTful Web Services

As park of this project imrlabs exposed much of the data for the mobile app through RESTful web services over JSON. The goal here was not to embed content in the app, but allow users always to receive the most up-to-date information directly from the web. If the web site updated content, then the app is updated as well. In order to accommodate iPod Touch users, and the fact that users in Disneyland don’t always have the greatest signal, caching is also employed. Here, through a paid upgrade, users and “sync” all the information available across the app for use offline.

Social Integration

An important aspect of any modern app is to provide direct integration with social networks such as Facebook. Here users can login directly through the app, and can optionally post status updates to Facebook when they submit a wait time for a Disneyland attraction, or when they submit a review. Facebook friends lists are also used so a user can view the activity of their friends who also are logged into the app.

For the Disneyland Inside Out project imrlabs also provided deep integration with Gowalla, who during App development, announced a partnership with Disney for location based check-ins at Disneyland and Walt Disney World. This announcement became a natural fit for inclusion in the app.

Server Side

In order to make an app like this successful, a strong server component is key. imrlabs was responsible for the development of all the server technologies as well. Here backend algorithms are used to filter submissions from users for content. Updates for content within the App are combined from various sources around the web and a detailed algorithm was built to estimate attraction wait times.